Post on 25-Jun-2020
Biophysical Modelling and Analysis of
Ecosystem Services in an Ecosystem
Accounting Context
DRAFT
Author: Lars Hein1
Version: 1 (9 December 2014)
This work was undertaken as part of the project Advancing the SEEA Experimental Ecosystem
Accounting. This note is part of a series of technical notes, developed as an input to the SEEA
Experimental Ecosystem Accounting Technical Guidance. The project is led by the United Nations
Statistics Division in collaboration with United Nations Environment Programme through its The
Economics of Ecosystems and Biodiversity Office, and the Secretariat of the Convention on
Biological Diversity. It is funded by the Norwegian Ministry of Foreign Affairs.
1The views and opinions expressed in this report are those of the author and do not necessarily reflect the
official policy or position of the United Nations or the Government of Norway.
ii
Contents 1. Introduction ......................................................................................................................................... 1
2. Biophysical accounting for ecosystem services .................................................................................. 2
2.1 Introduction ................................................................................................................................... 2
2.2 Concepts and indicators ................................................................................................................. 3
2.2.1 Ecosystem ............................................................................................................................... 3
2.2.2 Ecosystem services ................................................................................................................. 3
2.2.3 Ecosystems’ capacity to supply ecosystem services .............................................................. 4
3. Modelling ecosystem services in an accounting context ..................................................................... 6
3.1 Spatial modelling techniques ......................................................................................................... 6
3.2 Temporal modelling techniques .................................................................................................... 7
3.3 Modelling specific ecosystem services in an Accounting Context ............................................... 8
4. Global Datasets and remote sensing .................................................................................................. 11
4.1 Global datasets on ecosystem services analysis .......................................................................... 11
4.2 Global datasets on ecosystem components .................................................................................. 12
References ............................................................................................................................................. 15
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1. Introduction
This document provides guidance on the biophysical modelling and analysis of ecosystem service
flows and assets for the purpose of experimental ecosystem accounting. The document is prepared in
the context of the overall SEEA-Advancing Experimental Ecosystem Accounting project, building
upon and expanding earlier work in this field, and intends to provide a summary and review of
approaches, data, tools and results of existing and previous ecosystem accounting work focusing on
biophysical modelling. Compared to previous work eliciting how models can be used for ecosystem
accounting, this document provides an updated and extended analysis of how models can be applied.
The document pays specific attention to ensuring consistency with SNA principles, discusses both
temporal and spatial modelling approaches, discusses explicitly modelling for the purpose of asset
accounting, and includes a chapter (Chapter 4) that describes available data sources for ecosystem
modelling in an accounting context. This chapter includes a summary and review of how existing
global and national spatial datasets, including remote sensing imagery, such as the new Sentinel
satellites, can be applied in support of experimental ecosystem accounting.
Ecosystem accounting aims to analyze ecosystem services and ecosystem capital in a way that is
consistent with the national accounts. There is an increasing national and international interest in
ecosystem accounting, as expressed at the Rio plus 20 Conference and in a recent statement by the
European Union (EC, 2011). A first major step in the development of ecosystem accounting
procedures and guidelines was the ‘SEEA Experimental Ecosystem Accounting Guideline’
(EC/OECD/UN/World Bank, 2013). These guidelines lay out the basic concepts, the relation between
ecosystem accounting and environmental economic accounting and national accounting, as well as
remaining challenges in the development of ecosystem accounts. This document builds upon the
SEEA EEA guidelines, on the basis of experiences gathered with spatial and biophysical modelling of
ecosystem services as described in the scientific literature as well as national and global assessments
such as MA ( 2005), TEEB (2010), EC (2011), UK NEA (2011), SSCB (2014) and the recent IPBES
documents that are now becoming available.
Chapter 2 of the report first describes the general concepts underlying biophysical analysis of
ecosystem services in an accounting context. Chapter 3 focuses on the modelling of ecosystem
services. Finally, Chapter 4 analyses available global spatial datasets and how they, and the new
Sentinel satellites and other remote sensing resources, can be used in support of ecosystem accounting.
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2. Biophysical accounting for ecosystem services
2.1 Introduction
Ecosystem accounting provides information on the status of and trends in ecosystem capital, i.e. all
assets involving ecosystems (i.e. excluding sub-soil assets such as oil or ores). Once fully developed,
ecosystem accounts can serve as a satellite to the system of national accounts (SNA) in order to
provide information required for decision making on environmental and natural resource related
issues. The SNA (UN et al 2009) is an international statistical standard for the compilation of national
accounts, providing a comprehensive description of economic activity. The SNA accomplishes this by
describing the transactions (e.g. buying a product; or paying a tax) between institutional units such as
households or enterprises (Edens and Hein, 2013).
Ecosystem Accounting aims to includes a comprehensive set of ecosystem services (including
provisioning, regulating and cultural services), and to explicitly account for changes in the stock of
ecosystem capital (ecosystem assets). The stock of ecosystem capital is related to the capacity of the
ecosystem to generate ecosystem services at present and in the future, as further elaborated below. The
latter aspect also allows a systematic treatment and accounting for the degradation and rehabilitation
of ecosystems: these two aspects are reflected in the capacity of the ecosystem to provide services. In
this way, ecosystem accounting provides a comprehensive tool to analyze the sustainability of natural
resource use. Characteristic for Ecosystem Accounting is that a spatial approach is followed, in
recognition of the large spatial diversity of ecosystems and the services that they provide. A spatial
approach also facilitates the integration of ecological data (and data on ecosystem use) in the accounts.
As with ‘standard’ statistical approaches, a sampling strategy will often be required to analyze
ecosystem use and management. Contrary to most other economic activities, the spatial component of
ecosystems is crucial, scaling up of survey data requires consideration of the soils, climate, vegetation
etc. properties of the sampled location; scaling up without consideration of spatial ecological
variability will lead to substantial errors.
Constructing ecosystem accounts for multiple years allows measuring the degree of environmental
sustainability: a decline in ecosystem capital points to a decreasing capacity of ecosystems to sustain
human welfare over time. In addition, ecosystem accounting supports a number of additional policy
applications. For instance, ecosystem accounting can support land use planning or zoning by
identifying areas critical to the supply of specific ecosystem services. This is based on the spatial
approach followed in ecosystem accounting: ecosystem services flows, and the capacities of
ecosystems to generate services, are generally mapped for the specific areas for which an ecosystem
account is developed. Ecosystem accounting can also support the establishment of Payment schemes
for Ecosystem Services (PES), by identifying zones where the supply of a specific ecosystem service
is concentrated, or by laying out the co-benefits of PES mechanisms. Modelling ecosystem services
can takes place both to support data analysis required for ecosystem accounts (given the high spatial
variability of ecosystem services supply), and with the aim of supporting additional applications such
as Land Use Planning or developing PES schemes.
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2.2 Concepts and indicators
2.2.1 Ecosystem
The Convention on Biological Diversity defines an ecosystem as ‘a dynamic complex of plant, animal
and microorganism communities and the nonliving environment, interacting as a functional unit’.
Ecosystem dynamics and the supply of ecosystem services depend on the functioning of the ecosystem
as a whole, rather than on specific ecosystem components in isolation. Ecosystem accounting extends
to both natural and modified ecosystems. The distinction between the two systems, in practice, is not
always easy to make, usually there is a gradient in terms of intensity of ecosystem management, as in
the case of the gradient from fully managed, intensive rubber plantations to jungle rubber systems
(where farmers artificially increase hevea rubber trees in an otherwise natural forest) to tapping of
rubber in natural ecosystems as still practiced – albeit at a small scale - in the Amazon basin.
Ecosystem accounting aims to measure the contribution of ecosystems to economic activity, and this
contribution, in a relative sense, decreases with increasing intensity of human management. For
instance, in highly intensive systems all nutrients, water, seedlings, weed control, etc. are provided by
people. Where possible, indicators for ecosystem services need to be found that as much as possible
reflect the contribution of the ecosystem, and these indicators may well differ between ecosystems that
are defined as ‘natural’ or ‘human managed’ in the SNA. A still remaining question is if, in line with
the SNA, the contribution of the ecosystem in human managed systems should be measured in terms
of an increase in volume (for instance of standing timber), as in the SNA, or if the ecosystem services
should still be related to the harvest of use of the service at the time the service is actually used (e.g. in
the case of timber plantations the service only materializes at the moment in time the timber is
harvested).
2.2.2 Ecosystem services
Several slightly different definitions of ecosystem services have been provided (MA 2003; Boyd and
Banzhaf 2007; TEEB 2010; Bateman et al. 2010). A key issue is if ecosystem services are the benefits
provided by ecosystems (e.g. MA, 2003), or contributions to these benefits (e.g. TEEB, 2010). The
SEEA EEA guidelines provide the following definition of ecosystem services: ‘ecosystem services are
the contributions of ecosystems to benefits used in economic and other human activity’ (EC et al.,
2013). “Use” includes both the transformation of materials (e.g. use of timber to build houses or for
energy) and the passive receipt of non-material ecosystem services (e.g. amenity from viewing
landscapes). In the context of ecosystem accounting, two types of benefits can be distinguished: (i)
the products produced by economic units (e.g. food, water, clothing, shelter, recreation, etc.); and (ii)
the benefits that accrue to individuals that are not produced by economic units (e.g. clean air) (Edens
and Hein, 2013). The first category can be referred to as SNA benefits since the measurement
boundary is defined by the production boundary used to measure GDP in the System of National
Accounts (SNA). This includes goods produced by households for their own consumption. The second
category of benefits can be referred to as non-SNA benefits reflecting that the receipt of these benefits
by individuals is not the result of an economic production process defined within the SNA (Edens and
Hein, 2013).
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For all provisioning services, the contribution of the ecosystem needs to be combined with other inputs
in order to produce a tangible benefit. For instance, even though forests supply wood, labor and
equipment are needed in order to produce timber out of standing wood. Or, landed fish require both
the presence of fish in the sea (the ecosystem service) and the activities of people in order to harvest
these fish. The costs of these activities need to be deducted in the monetary valuation of the ecosystem
service, following the appropriate methods. For other services, the distinction between service and
benefit may be less pronounced. For instance, carbon sequestration also occurs in natural forests
regardless of any human intervention. In this case, the service equals the benefit. In the case of a
carbon sequestration through reforestation project, however, the generation of the service may require
human activities such as planting seedlings, irrigation of immature trees, soil management, etc. In this
case there is a clear distinction between the service and the benefit. Even though the service and the
benefit are, as in the case of some provisioning services such as crop production, difficult to
disentangle, in monetary terms the distinction is clear: in case of reforestation projects for carbon
sequestration the costs of planting and tending the trees need to be deducted in order to obtain the
monetary value of the service.
Likewise, the cultural service related to ecotourism may occur in areas that are strongly shaped by
people, e.g. to construct walking paths, visitors facilities, and involving guides, or it may take place in
fully natural areas. The contribution of the ecosystem is, essentially, providing opportunities for
recreation and tourism, which in the first example involved human activities in order to generate or
enhance those opportunities. Monetary valuation of the two services would need to consider the costs
of preparing and maintaining hiking paths and visitor facilities.
In Ecosystem Accounting, the principle should be that the ecosystem service is the flow/output most
directly connected to the ecosystem (e.g. the standing stock of timber that is harvested or the grass that
is extracted from the pasture), while recognizing that this flow is, in the case of many ecosystems, the
consequence of a combination of natural/ecological processes and man-made inputs (Edens and Hein,
2013). For crop production, the ecosystem service has been defined as the contribution of the
ecosystem to crop production in the form of nutrient retention and supply, water retention and supply,
and providing a substrate for cultivation (EC et al., 2013). Since these different aspects are difficult to
quantify and express in one or a small set of indicators, the current working hypothesis established in
discussions that took place in the context of (EC et al., 2013) is that the service crop production can
be approximated in physical terms in terms of the amounts of crops produced, and that valuation needs
to account for the whole set of human inputs into crop production, following a resource rent approach.
2.2.3 Ecosystems’ capacity to supply ecosystem services
Provisioning services. In general terms, the capacity of an ecosystem to provide ecosystem services
depends on the area covered by an ecosystem (its extent), and the condition of the ecosystem (its
quality) (SEEA EEA – 1.53). The capacity of the ecosystem asset to continue to generate ecosystem
services into the future will change as a function of changes in the condition and extent of the
ecosystem asset and in response to changes in the expected flows of ecosystem services (EC et al.,
2013). While ecosystem condition may be assessed without considering measures of ecosystem
services, the measurement of ecosystem assets in terms of their capacity to generate ecosystem
services must involve assessment of ecosystem condition, for instance soil fertility and rainfall
influence regrowth of standing stock of timber following timber harvest. Note that capacity can be
defined per accounting unit (e.g. per Land Cover Ecosystem Unit) or per EAU (Ecosystem Accounting
5
Unit) and in terms of capacity of each Basic Spatial Unit to generate an ecosystem services (e.g. the
capacity of a pixel in a GIS model). Aggregating capacities of individual pixels (/BSUs) over an
LCEU gives the capacity per LCEU, and aggregation over an EAU provides the capacity of the EAU
to supply a specific service.
Capacity may be aligned with the concept of sustainable yield, in the case of a single resource (e.g. a
fish stock) (SEEA EEA 2.32). The sustainable yield, in turn, is determined by the opening stock of the
resource (e.g. the fish stock), the growth rate of the resource (e.g. the increase in fish stock due to
replenishment) and the loss of fish due to natural processes (e.g. climate variability). However, in
reality, single resource use in ecosystems is very rare, many ecosystems provide a basket of goods and
services. Hence, in general the capacity to generate provisioning services can be defined on the basis
of the long-term capacity of the ecosystem to supply services based on current land use, management
and climate (EC et al., 2013). A comprehensive approach is required to establish the capacity. For
instance, in the case of timber production (an activity), using timber stands naturally grown in the
forest ecosystem (the service), the capacity of the forest at a given time to sustain timber harvesting in
the future is a function of the standing stock of timber and the regenerative capacity of the forest (i.e.
the mean annual increment, which is in turn determined by among others the age of the trees, soil
fertility, water availability, temperature, fire incidence, and potentially management of the forest).
The supply of individual services is often related. For instance, timber extraction at a maximum
sustainable rate (a rate that would not jeopardize future timber harvest) may lead to negative effects on
biodiversity conservation or carbon sequestration. This indicates that the extraction rate used as a
benchmark for sustainable extraction varies for different types of services and land use, and needs to
be defined based on locally relevant conditions. The basic principle should be to analyze capacities for
all ecosystem services individually based on current management practices. An important implication
is that the value of an asset as included in the Ecosystem Accounts is by no means necessarily equal to
the maximum value that can be generated by an ecosystem.
Regulating services. Regulating service can be interpreted as involving the generation of a positive
externality. The capacity becomes a flow if there are people benefiting from this capacity (aligned
with the modelling of ecosystem services in for instance within the ARIES2 modeling framework
(Villa et al. 2014). For instance, in this interpretation, erosion control is a capacity wherever it occurs,
and this environmental process becomes an ecosystem service flow if there are people living in the
area that experiences a reduction in erosion risk (e.g. who live in the area downslope where mudflows
do not, or less occur because of vegetation upslope). Carbon sequestration is a peculiar service,
because people always benefit from this service, and for this service capacity equals flow (in line with
Schröter et al., 2014).
A particular issue with regulating services is that there can also be a disservice, i.e. services with a
negative value, e.g. involving carbon emissions form a degraded peatland, or pest and diseases from
ecosystems. Services with a negative value are difficult to accommodate in an accounting context
(although there is a potential opening to include negative services in an account when these regulating
services are considered to be generated by the sector ecosystems rather than through the activity of a
specific sector that uses ecosystems as an asset (see Edens and Hein 2013 for details)). The disservices
can be the opposite (in terms of direction) flow of the service, as in the case of carbon emissions from
drained peatlands. The flux of carbon from drained peat is from the ecosystem to the atmosphere, the
2 Artificial Intelligence for Ecosystem Services (http://www.ARIESonline.org/)
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sequestration of carbon by forests on mineral soil involves a flux from the atmosphere to the
ecosystem. Considering these disservices is important in view of their relative economic importance,
their importance for policy making (e.g. REDD+) and the potential occurrence of services and related
disservices within the same institutional unit (World Bank, 2014). In the paper ‘Linking asset and flow
accounts’ it is analyzed how services and selected disservices can be included in the accounts.
Cultural services. Cultural services range from tourism and recreation to spiritual aspects and
biodiversity conservation. The capacity of the service needs to be defined and determined for each
specific service individually. For recreation and tourism, it may relate to the amount of tourists that
can potentially be accommodated in a specific area as a function of the level of interest in the type of
ecosystem involved, the level of access / remoteness, etc. In case there are grounds to assume that the
number of tourists may increase in the future the capacity could be assumed to increase accordingly
(World Bank, 2014). For biodiversity conservation, capacity may be related to the species numbers
that an area can sustainably harbor under current land use and land cover. The capacity may be higher
than the actual occurrence of the species (e.g. because of high hunting pressure) or lower (e.g. because
the area is a refuge and current population numbers are above the number that can be sustained in the
long-term).
3. Modelling ecosystem services in an accounting context
3.1 Spatial modelling techniques
Spatial modelling is required to produce wall-to-wall maps of ecosystem services for the overall
Ecosystem Accounting Unit, covering the different aspects of ecosystem condition, capacity and
ecosystem service flows. Often, data is lacking for some areas, for some specific indicators. In this
case, spatial interpolation and/or modelling techniques can be used to produce comprehensive maps.
This would normally require the combination of a range of datasets including remote sensing images,
thematic maps, surveys for specific administrative or ecological units, and point data from specific
studies. The different datasets used need to be spatially defined, i.e. they need to be attributed to a
spatially defined reference location using a relevant coordinate system – either in case of point data or
in case a map is used. Sometimes countries have a specific coordinating system applied in their
statistical agencies in which case it is beneficial to use the same coordinate system.
There are a range of spatial modeling tools available for the modelling of ecosystem services. The
simplest is called the ‘Look-up Tables’ approach. More sophisticated methods allow for extrapolation
of data to missing points, as well as more elaborate statistical or process based modeling of services
supply. In the lookup tables approach, specific values for an ecosystem service or other variable are
attributed to every pixel in a certain class, usually a land cover or land use class. These values need to
be derived from the scientific literature, for ecosystems that are comparable in terms of vegetation,
soil, climate, etc. For instance, every pixel in the land cover class ‘deciduous forest’ could be given a
specific value for its carbon stock, say 250 ton C/ha, based on studies that analyzed the carbon
contents of this forest type in a specific agro-ecological zone. In general, the more homogeneous the
class is, the more accurate a LUT approach will be.
In addition, there are several statistical approaches for spatial modelling of ecosystem services,
capacity and condition, with Maxent being relatively user friendly in the context of ecosystem
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accounting. Maxent (Phillips et al., 2006) stands for Maximum Entropy, and has traditionally been
used to map habitat for different species. The model predicts the potential of a species or ecosystem
attribute occurrence by “finding the distribution of maximum entropy (i.e. closest to uniform) subject
to the constraint that the expected value of each environmental variable under this estimated
distribution matches its empirical average” (Philips et al., 2006). Maxent requires only presence
points, and the accuracy levels can also be calculated (using the area under receiver operating
characteristic (ROC) curve (AUC), whose value ranges from 0 to 1; an AUC of 1 indicates a perfect
accuracy).
Geostatistical interpolation techniques such as kriging rely on statistical algorithms to predict the value
of un-sampled pixels on the basis of nearby pixels in combination with other characteristics of the
pixel. The basic interpolation methods use simple interpolation algorithms, for instance nearest-
neighbor interpolation, but there are more sophisticated geostatistic tools that also considers sets of
correlated variables. For instance, timber productivity may be related to productivity in nearby pixels,
but in a more comprehensive approach it may also be related to factors such as soil fertility or water
availability for which spatial maps are available. Critical in applying geostatistics is that a sufficiently
large sample size is available, and that samples are representative of the overall spatial variability
found.
3.2 Temporal modelling techniques
In SEEA EEA, temporal modelling is required to forecast the capacity of the ecosystem to generate
ecosystem services over time. In particular, the ecosystem asset depends upon the capacity to
generate ecosystem services over time. This capacity is a function of the standing stock (e.g. of a
timber stand), the regrowth due to natural processes (e.g. growth in timber volume due to regrowth of
the forest following harvesting), losses due to natural processes (e.g. storm damage) and ecosystem
management (e.g. fire control, pruning, etc.). If the asset is valued in monetary terms, the asset value
reflects the Net Present Value (NPV) of the expected flow of ecosystem services (e.g. the discounted
net value of the flow of timber during the discounting period). Hence, the flow of timber (and other
ecosystem services) needs to be modelled, for every accounting unit.
The modelling approach most consistent with coming to an understanding of flows of ecosystem
services is a dynamic systems approach. This approach is based upon the modelling of a set of state
(level) and flow (rate) variables in order to capture the state of the ecosystem, including relevant
inputs, throughputs and outputs, over time. Dynamic systems models use a set of equations linking
ecosystem state, management and flows of services. A dynamic systems model contains state and
flow indicators and variables that capture, for instance, the amount of standing biomass (state), the
harvest of wood (flow), and the price of wood (time dependent variable). The models runs on the
basis of predefined time-increments and requires fully defined initial conditions. The systems
approach can contain non-linear dynamic processes, feedback mechanisms and control strategies, and
can therefore deal with complex ecosystem dynamics, which are discussed below. However, it is often
a challenge to understand these complex dynamics, and their spatial variability, and data shortages
may be a concern in the context of ecosystem accounting that requires large scale analysis of
ecosystem dynamics and forecasted flows of ecosystem services.
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Complex ecosystem dynamics include irreversible and/or non-linear changes in the ecosystem as a
response to ecological or human drivers. Irreversible changes in ecosystems occur when the
ecosystem is not, by itself, able to recover to its original state following a certain disturbance.
Multiple states are relatively stable configurations of the ecosystem, caused by the existence of
feedback mechanisms that reinforce the system to be in a particular state. In addition, the ecosystem
may also develop as a consequence of stochastic natural conditions, for instance when ecosystem
change is driven by fires or high rainfall events. These complex dynamics occur in a wide range of
ecosystems, and have a major impact on the future flows of ecosystem services. Where possible
(pending data and understanding of the ecological processes involved), these aspects should be
considered in the Ecosystem Asset Account.
In some cases, spatial and temporal modelling approaches need to be combined. For instance, process
based models are generally required to model regulating services such as erosion control, or ground
and surface water flows. Erosion, and erosion control is often modelled with the USLE approach (even
though it’s reliability outside of the part of the world was developed (i.e. the US) has proven to be
variable). Other examples of process based models are the hydrological models such as SWAT and
(CSIRO) SedNet. These models are both temporally and spatially explicit, using a dynamic systems
modelling approach integrated in a GIS (for instance using the Python modelling language). SWAT is
one of the most widely used hydrological models, and uses Hydrological Response Units (HRUs) to
model water flows and water stocks, and the processing taking place within these units. The model
operates with daily time steps and can therefore be used to model flood regulation throughout the year
(through retention of water in upstream HRUs) and maintenance of dry season water flow (through
retention and gradual release of water in upstream HRUs). In order to link land use change to
hydrology, SWAT needs to be extended with a landscape module, that allows modelling and
integration of overland processes such as run-off and run-on and the deposition of soil particles in
streams and waterways. SWAT also allows a range of processes affecting water quality such as
denitrification.
Note that a critical aspect of modelling hydrological flows is the resolution of the model, both in space
and in time. The required resolution depends upon the study area and the geomorphology of the study
area, and the selection of the resolution will also be influenced by the availability of data. In general,
to have an ecologically robust modelling of water flows, a spatial resolution of at most 30 meters
(corresponding to the global ASTER Digital Elevation Model3) is recommendable. A temporal
resolution of a day would also be recommendable in order to understand and calibrate water flows
over time, including the capacity of ecosystems to store water in support of downstream flood control
or dry season water supply. Models that use a temporal resolution of months or even years (such as the
current InVEST hydrology module) would not generally be adequate to model this service.
3.3 Modelling specific ecosystem services in an Accounting Context
This section presents a very general introduction to the different approaches that can be used to map
specific services. The specific modelling approaches applicable to different areas, however, need to be
defined as a function of the ecosystem, ecosystem services, ecosystem management, data availability,
and the environmental and social context involved (see also World Bank, 2014).
3 Note that the local accuracy of the global ASTER DEM dataset may vary for different parts of the planet, see
also Table 4 of this report.
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Table 1. Indicators and mapping methods for selected ecosystem services
Service Potential indicator Description
Carbon
storage
Ton of carbon (or
carbon-dioxide) per
hectare or square
kilometer.
Carbon storage includes storage in vegetation (above ground,
root, dead wood, and litter carbon) and soil carbon. Soil carbon
may be low compared to vegetation carbon, as in some types of
poor fertility tropical forest soils, or it may be by far the largest
component of total carbon storage, as in peatland soils in deep
peat (World Bank, 2014). Above ground carbon can be
measured with radar remote sensing, but the measurement of
below-ground carbon with optical techniques is generally not
possible. Instead, for this part of the carbon stock, soil sampling
and interpolation of data points is required. Carbon maps are
increasingly available for different parts of the world (see also
Chapter 4), and the capacity to map above ground carbon stock
globally will also increase with the launch of the Sentinel radar
satellite in 2014.
Carbon
sequestration
Ton of carbon (or
carbon-dioxide)
sequestered per
year, per hectare or
per square
kilometer.
Carbon sequestration can be related to net ecosystem
productivity (NEP), i.e. the difference between net primary
productivity (NPP) and soil respiration. NPP can be derived
from the Normalized Difference Vegetation Index (NDVI) that
can be measured with remote sensing images. However care
needs to be taken that the relation between NDVI and NPP is
well established for the ecosystems involved, and that accuracy
levels are calculated based on sample points. It is often difficult
to find credible values for the spatially very variable soil
respiration rate, which depends on bacterial and fungi activity
which are in turn guided by the local availability of organic
matter (e.g. fallen leaves), temperature, moisture, etc.
Maintaining
rainfall
patterns
mm water
evapotranspiration
per hectare per
year, mm rainfall
generated per
hectare per year.
Rainfall patterns depend on vegetation patterns at large scales.
For instance, it has been estimated that maintaining rainfall
patterns in the Amazon at current levels requires maintaining at
least some 30% of the forest cover in the basin. Reductions in
rainfall in the Western Sahel and the Murray Basin in Australia
have also been correlated to past losses of forest cover. This is a
significant ecosystem service, however the value of individual
pixels is difficult to establish since it requires understanding
large scale, complex climatological patterns, large scale
analyses of potential damage costs, and interpolations of values
generated at large scales to individual pixels with detailed
climate-biosphere models.
Water
regulation
- water storage
capacity in the
ecosystem in m3
per hectare (or in
mm);
- difference
Water regulation includes several different aspects, including (i)
flood control; (ii) maintaining dry season flows; and (iii) water
quality control – e.g. by trapping sediments and reducing
siltation rates). Temporal, i.e. inter-annual and intra-annual,
variation is particularly important for this service. Modelling
this service is often data-intensive and also analytically
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between rainfall
and evapo-
transpiration in
m3/ha/year;
complex. SWAT is a model often used to model this kind of
flows, however extensions of the SWAT model are needed to
link land use to water flows, see also Chapter 4.
Surface
water
modelling;
Flood
protection
Surface water
modelling can be
deployed to analyze
reductions in flood
risk, expressed
either as reduction
in probability of
occurrence,
reduction in
average duration of
the flood, or
reduction in water
level depending on
context
Flood protection depends on linear elements in the landscape
that act as a buffer against high water levels (e.g. a mangrove,
dune or riparian system). Modelling this service requires
modelling flood patterns and the influence of the vegetation. It
may not always be needed to model flood protection in physical
terms in order to understand the monetary value of the service -
in particular in those areas where it is certain that natural
systems, if lost, would be replaced by artificial ones (e.g. a
dyke), as would be the case in most of the Netherlands, for
instance. In this case, valuation may be done on the basis of a
replacement cost approach that does not require understanding
the physical service in full.
Erosion and
sedimentatio
n control
- difference
between sediment
run-off and
sediment deposition
in ton/ha/year
There is relatively much experience with modelling this service.
Erosion models can be integrated in a catchment hydrological
models (such as SWAT or CSIRO SedNet, both freeware) to
predict sediment rates. In SWAT, a watershed is divided into
Hydrological Response Units (HRUs), representing
homogeneous land use, management, and soil characteristics.
Erosion rates need to be estimated for each HRU, for instance
on the basis of the MUSLE or RUSLE erosion models or
alternatively SWAT landscape can be used which includes grid
based land cover units.
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4. Global Datasets and remote sensing
4.1 Global datasets on ecosystem services analysis
There are several databases providing information on ecosystem services and their values, both spatial
and non-spatial (Table 2 below) as well as a number of global tools that provide information on the
methods that can be used to map, model or value ecosystem services (presented in Table 3 below).
Table 2. Global ecosystem services databases
Dataset Author Description Scale Link
Pilot Analysis of
Global Ecosystems
(PAGE): Agro-
ecosystems
World Resources
Institute (WRI),
IFPRI
The study
identifies linkages
between crop
production systems
and environmental
services such as
food, soil
resources, water,
biodiversity, and
carbon cycling
9 geospatial
datasets providing
a detailed spatial
perspective on
agroecosystems
and agroecosystem
services, see Annex
1.
http://www.ifpri.org/
dataset/pilot-analysis-global-
ecosystems- page (187 Mb)
Ecosystem Services
Values Database
FSD, Wageningen Database
containing
information on
valuation studies
carried out across
the planet (value
estimates, authors
of studies, general
description of
methodology
used).
Non-spatial. http://www.fsd.nl/esp/80763/5/0/50
Table 3. Databases with methods for ecosystem service assessment Dataset Author Description Link
Values
Database
Deutsche Gesellschaft für
internationale Zusammenarbeit
(GIZ) GmbH;
Helmholtz-Zentrum für
Umweltforschung
(UFZ) GmbH
Database with
detailed
description of
modelling
methods and
valuation
approaches
http://www.aboutvalues.net/
method_database/
Ecosystemv
aluation.org
University of Maryland Database with
information
on and
examples of
valuation
methods
www.ecosystemvaluation.org
12
4.2 Global datasets on ecosystem components
Table 4 below describes some of the key datasets with a global cover that are relevant for ecosystem
accounting, subdivided into datasets covering remote sensing data, land cover and vegetation, soils
and water. Note that these datasets are usually derived from remote sensing data in combination with
other datasets. The table only lists datasets that can be downloaded free of charge, with commercial
datasets usually available at higher resolution, but requiring payment for specific geographical areas.
Note that the data from the new European Space Agency Sentinel satellites is not yet available. Their
resolution is finer than the Landsat images, and an additional advantage is that the satellites provide
both radar and optical images. Note that a total of 6 Sentinel satellites are planned to be launched, with
Sentinel 1 (Radar) and Sentinel 2 (Optical) most relevant for Ecosystem Accounting. Note also that
remote sensing data provides information on the observable properties of ecosystems. Some of this
information can be linked to ecosystem uses (i.e. ecosystem service flows), such as information on
deforestation patens or land use change. Other observable information can be linked to Ecosystem
assets (such as standing biomass or Net Primary Production). The specific linkage of remote sensing
data to ecosystem service flow or asset modelling always needs to be determined for the specific
ecology and uses of the area involved. state of This would lead to a large increase in possibilities to
model land cover and model ecosystem services such as crop production, carbon sequestration
(through fine resolution NPP mapping) and erosion control (e.g. by modelling vegetation cover of the
soil). Given that data volumes are large this means that larger data storage and processing facilities
will be needed to deal with the information generated. Specific information on potential applications
of Sentinel imagery can only be provided when the images become available (currently estimated to be
early 2015 for the radar images).
Table 4. Global datasets
Dataset Author Description Scale Link
Remote sensing data
MODIS
imagery
dataset
NASA
Earth
Observatio
n System
(EOS)
Views the entire surface of
the Earth every one to two
days, imagery can be
downloaded from website.
Its detectors measure 36
spectral bands between
0.405 and 14.385 µm, and
it acquires data at three
spatial resolutions --
250m, 500m, and 1,000m.
https://lpdaac.usgs.gov/products
Landsat
dataset
NASA Multispectral data of the
Earth’s surface on a global
basis, from several
operational Landsat
satellites (plus historical
images form earlier Landsat
satellites).
Depending on satellite
and band, for Landsat 8
has 11 bands with a
resolution of 30 by 30
meter for 8 out of these 11
bands.
http://landsat.gsfc.nasa.gov/
Sentinel European
Space
Agency
■Sentinel-1 is a polar-
orbiting, all-weather, day-
and-night radar imaging
mission for land and ocean
services. The first Sentinel-1
satellite was launched on 3
April 2014.
■Sentinel-2 is a polar-
orbiting, multispectral high-
resolution imaging mission
for land monitoring to
provide, for example,
Wide-swath mode at 250
km and 5×20 m resolution
Wave-mode images of
20×20 km and 5×5 m
resolution (at 100 km
intervals)
Strip map mode at 80 km
swath and 5×5 m
resolution
Extra wide-swath mode of
400 km and 20×40 m
resolution
At the time of preparation of this
document, the Sentinel data were
not yet available. More
information can be found at:
http://www.esa.int/Our_Activitie
s/Observing_the_Earth
13
imagery of vegetation, soil
and water cover, inland
waterways and coastal
areas.
Land cover and vegetation
Global Index
of
Vegetation-
Plot
Databases
(GIVD)
Metadatabase providing an
overview of existing
vegetation data worldwide,
the metadatabase facilitates
the use of these data by
other scientists.
www.givd.info
The Global
Land Cover
2000 Map
EU Joint
Research
Centre
The map illustrates the
distribution of surface
materials or “land cover”
over the entire globe. This
map helps to show the
major ecological systems
that exist such as forests,
grasslands, and cultivated
areas.
Published in geographic
projection at 30 arc-
seconds resolution.
http://geoserver.isciences.com:80
80
/geonetwork/srv/en/metadata.sho
w?id=55
MODIS NPP
dataset
NASA
Earth
Observatio
n System
(EOS)
Continuous estimates of
Gross/Net Primary
Production (GPP/NPP)
across Earth’s entire
vegetated land surface.
Useful for natural resource
and land management,
global carbon cycle
analysis, ecosystem status
assessment, and
environmental change
monitoring.
1 km resolution http://www.ntsg.umt.edu/project/
mod17
Global
Forest
Change
2000–2012
University
of
Maryland
Results from time-series
analysis of 654,178 Landsat
7 ETM+ images in
characterizing global forest
extent and change from
2000 through 2012. For
additional information about
these results, please see the
associated journal article
(Hansen et al., Science
2013).
1 km resolution (note that
the maps sometimes
classifies plantations such
as palm oil plantations as
forests)
http://www.earthenginepartners.a
ppspot.com/science-2013-global-
forest/download.html
Global
Forest
Resources
Assessment
2010 (also
available for
1990, 2000,
2005)
FAO Comprehensive assessment
of forests and forestry
examining the current status
and recent trends for about
90 variables covering the
extent, condition, uses and
values of forests and other
wooded land,
Not spatial, information is
presented in tables per
country. The reliability
and accuracy of the tables
varies per country.
http://www.fao.org/forestry/fra/fr
a2010/en/
Soils and terrain
SoilGrid ISRIC
Wagening
en
Dominant soil types
according to FAO/ISRIC
soil classification
1 km grid, global. http://www.isric.org/content/soilg
rids
14
ASTER
Global
Digital
Elevation
Map
NASA,
METI
Japan
DEM and water body
coverage and detection in
GeoTIFF format
30-meter postings and 1 x
1 degree tiles
http://asterweb.jpl.nasa.gov/gdem
.asp
Water
Tropical
Rainfall
Measuring
Mission
(TRMM)
NASA and
JAXA
Precipitation
over tropical and
subtropical regions
From around 35° north
latitude (e.g., the
Mediterranean Sea) to 35°
south latitude (e.g.,
the southern tip of South
Africa), since 1997
http://trmm.gsfc.nasa.gov/overvie
w_dir/background.html
Global
Precipitation
measurement
NASA Observations of rain and
snow worldwide every
three hours
Global, from 65° north
latitude (e.g., the Arctic
Circle) to 65° south
latitude. This is a new
satellite, and information
is now becoming
available.
http://www.nasa.gov/mission_pa
ges/GPM/main/
WaterWorld King's
College
London
(models),
Ambio-TEK
(software)
Rainfall and potential
evapotranspiration rates,
global dataset
1 km grid http://www.policysupport.org/
waterworld
15
References
Ansink, E., Hein, L., Hasund, K.P., 2008. To value functions or services? An analysis of ecosystem
valuation approaches. Environmental Values 17, 489–503.
Arshad, M.A., Martin, S., 2002. Identifying critical limits for soil quality indicators in agroecosystems.
Agricullture Ecosystems and Environment 88, 153–160.
Banzhaf, S., Boyd, J., 2012. The architecture and Measurement of an Ecosystem Services Index.
Sustainability 2012, 4.
Campos, P., F. Bonnieux , A. Caparros JC Paoli, 2007. Measuring total sustainable incomes from
multifunctional management of Corsican Maritime Pine and Andalusian Cork oak Mediterranean forests.
Journal of Environmental Planning and Management 50:1, 65-85.
Daily, G.C., Polasky, S., Goldstein, J., Kareiva, P.M., Mooney, H.A., Pejchar, L., Ricketts, T.H., Salzman,
J., Shallenberger, R., 2009. Ecosystem services in decision making: time to deliver. Frontiers in Ecology
and the Environment 7, 21–28.
Egoh B, Drakou EG, Dunbar MB, Maes J, Willemen L, 2012. Indicators for mapping ecosystem services:
a review. Report EU.
European Commission, International Monetary Fund, Organisation for Economic Co-operation and
Development, United Nations, World Bank, 2013. Experimental Ecosystem accounting Guidelines.
European Commission, 2011. Our life insurance, our natural capital: an EU biodiversity strategy to 2020,
244. COM, Brussels (3.5.2011).
European Commission, 2013. Mapping and Assessment of Ecosystems and their Services, An analytical
framework for ecosystem assessments under Action 5 of the EU Biodiversity Strategy to 2020.
Edens, B. and L. Hein, 2013. Towards a consistent approach for Ecosystem Accounting. Ecological
Economics 90, 41-52.
Lonsdorf, E., C. Kremen, T.Ricketts et al., 2009. Modelling pollination services across agricultural
landscapes. Annals of Botany 103, 1589-1600.
Hein, L. 2014. ‘Linkages between ecosystems asset accounts and ecosystem service accounts ‘, Short
Paper prepared for UNSD, New York.
MA, 2003. Ecosystems and Human Well-being: A Framework for Assessment. Millennium Ecosystem
Assessment. Island Press, Washington, D.C., USA.
MA, 2005. Ecosystems and human well-being: current state and trends. Millennium Ecosystem
Assessment, Island Press, Washington, D.C., USA.
Martnez-Harms MJ & Balvanera P, 2012. Methods for mapping ecosystem service supply: A review.
International Journal of Biodiversity Science, Ecosystems Services and Management 8, 17-25
16
Phillips SJ, Anderson RP, Schapire RP (2006) Maximum entropy modeling of species geographic
distributions. Ecological Modelling 190 (3–4): 231–259
Potter, C., Randerson, J., Field, C., Matson, P., Vitousek, P., Mooney, H., Klooster, S., 1993. Terrestrial
ecosystem production: a process model based on global satellite and surface data. Global Biogeochemical
Cycles 7, 811–841.
Remme, RP M Schröter, L Hein, 2014. Developing spatial biophysical accounting for multiple
ecosystem services. Ecosystem Services 10, 6-18
Ricketts, T.H., Daily, G.C., Ehrlich, P.R., Michener, C.D., 2004. Economic value of tropical forest to
coffee production. PNAS 101, 12579–12582.
Secretariat for the Convention on Biological Diversity, 2014. CBD Technical Series No. 77
ECOSYSTEM NATURAL CAPITAL ACCOUNTS: A Quick Start Package.
Schröter, M., D. Barton, RP. Remme, L Hein, 2014. Accounting for capacity and flow of ecosystem
services: A conceptual model and a case study for Telemark, Norway. Ecological Indicators 36, 539-551.
Sumarga, E. L Hein, 2014. Mapping Ecosystem Services for Land Use Planning, the Case of Central
Kalimantan. Environmental management, 1-14
TEEB, 2010. The economics of ecosystems and biodiversity. Mainstreaming the economics of nature. A
synthesis of the approach, conclusions and recommendations of TEEB. (www.teebweb.org).
Thrush, S.F., Hewitt, J.E., Dayton, P.K., Coco, G., Lohrer, A.M., Norkko, A., 2009. Forecasting the Limits
of Resilience: Integrating Empirical Research With Theory. Proc. R.Soc. B: Biol Sci 3209–3217.
UK National Ecosystem Assessment, 2011. The UK National Ecosystem Assessment, Synthesis of the Key
Findings.UNEP-WCMC, Cambridge.
United Nations, 1992. Convention on Biological Diversity.
United Nations, 1993. Handbook of National Accounting. Integrated Environmental and Economic
Accounting, New York.
United Nations, European Commission, International Monetary Fund, Organisation for Economic Co-
operation and Development, World Bank, 2013. Handbook of National Accounting: Integrated
Environmental and Economic Accounting 2013.
Van Oudenhoven, A.P.E., Petz, K., Alkemade, R., Hein, L., de Groot, R.S., 2012. Framework for
systematic indicator selection to assess effects of land management on ecosystem services. Ecological
Indicators 21, 110–122.
Villa F., Bagstad K.J., Voigt, B., Johnson G.W., Portela R., Honzák M., Batker D. (2014) A Methodology
for Adaptable and Robust Ecosystem Services Assessment. PLoS One (forthcoming).
World Bank, 2014. Designing Pilots for Ecosystem Accounting. World Bank WAVES project, May 2014,
Washington DC.